Selection of the Optimal Microelectrode During DBS Surgery in Parkinson's Patients

Konrad Andrzej Ciecierski , Zbigniew W. Raś , Andrzej W. Przybyszewski

Abstract

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is effective treatment of Parkinson disease. Because the STN is small (9 x 7 x 4mm) and it is not well visible using conventional imaging techniques, multi-microelectrode recordings are used to ensure accurate detection of the STN borders. Commonly used discriminations which microelectrode’s signal relates to the activity of the STN are signal quality and neurologist’s experience dependent. The purpose of this paper is to determine the STN coordinates in a more objective way. We present analysis of the neurological signals acquired during DBS surgeries. The purpose of our method is to discover which one of the scanning microelectrodes reaches the target area guaranteeing a most successful surgery. Signals acquired from microelectrodes are first filtered. Subsequently the spikes are detected and classified. After that, new signal is reconstructed from spikes. This signal’s power is then calculated by means of FFT. Finally cumulative sum of the signal’s power is used to choose a proper electrode. The ultimate goal of our research is to build a decision support system for the DBS surgery. A successful strategy showing which of the recording microelectrodes should be replaced by the DBS electrode is probably the most difficult and challenging.
Author Konrad Andrzej Ciecierski II
Konrad Andrzej Ciecierski,,
- The Institute of Computer Science
, Zbigniew W. Raś II
Zbigniew W. Raś,,
- The Institute of Computer Science
, Andrzej W. Przybyszewski
Andrzej W. Przybyszewski,,
-
Pages554-564
Book Kryszkiewicz Marzena, Rybiński Henryk, Skowron Andrzej, Raś Zbigniew W. (eds.): Foundations of Intelligent Systems, Lecture Notes in Artificial Intelligence, vol. 6804, 2011, Springer, ISBN 978-3-642-21915-3, 746 p., DOI:10.1007/978-3-642-21916-0
Keywords in EnglishParkinson’s disease, DBS, STN, wavelet, filtering, PCA, FFT, spike detection, spike discrimination, spike clustering
DOIDOI:10.1007/978-3-642-21916-0_59
projectDevelopment of new methods and algorithms in the following areas: computer graphics, artificial intelligence, and information systems; and distributed systems. Project leader: Rybiński Henryk, , Phone: +48 22 234 7731, start date 24-06-2010, planned end date 31-12-2010, end date 30-11-2011, II/2010/DS/1, Completed
WEiTI Działalność statutowa
Languageen angielski
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Score (nominal)10
Citation count*6 (2018-02-21)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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